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| # this file is only for batch size search and is not used for training | |
| # Define dataset | |
| dataset = dict( | |
| type="VariableVideoTextDataset", | |
| data_path=None, | |
| num_frames=None, | |
| frame_interval=3, | |
| image_size=(None, None), | |
| transform_name="resize_crop", | |
| ) | |
| # bucket config format: | |
| # 1. { resolution: {num_frames: (prob, batch_size)} }, in this case batch_size is ignored when searching | |
| # 2. { resolution: {num_frames: (prob, (max_batch_size, ))} }, batch_size is searched in the range [batch_size_start, max_batch_size), batch_size_start is configured via CLI | |
| # 3. { resolution: {num_frames: (prob, (min_batch_size, max_batch_size))} }, batch_size is searched in the range [min_batch_size, max_batch_size) | |
| # 4. { resolution: {num_frames: (prob, (min_batch_size, max_batch_size, step_size))} }, batch_size is searched in the range [min_batch_size, max_batch_size) with step_size (grid search) | |
| # 5. { resolution: {num_frames: (0.0, None)} }, this bucket will not be used | |
| bucket_config = { | |
| # == manual search == | |
| # "240p": {128: (1.0, 2)}, # 4.28s/it | |
| # "240p": {64: (1.0, 4)}, | |
| # "240p": {32: (1.0, 8)}, # 4.6s/it | |
| # "240p": {16: (1.0, 16)}, # 4.6s/it | |
| # "480p": {16: (1.0, 4)}, # 4.6s/it | |
| # "720p": {16: (1.0, 2)}, # 5.89s/it | |
| # "256": {1: (1.0, 256)}, # 4.5s/it | |
| # "512": {1: (1.0, 96)}, # 4.7s/it | |
| # "512": {1: (1.0, 128)}, # 6.3s/it | |
| # "480p": {1: (1.0, 50)}, # 4.0s/it | |
| # "1024": {1: (1.0, 32)}, # 6.8s/it | |
| # "1024": {1: (1.0, 20)}, # 4.3s/it | |
| # "1080p": {1: (1.0, 16)}, # 8.6s/it | |
| # "1080p": {1: (1.0, 8)}, # 4.4s/it | |
| # == stage 2 == | |
| # "240p": { | |
| # 16: (1.0, (2, 32)), | |
| # 32: (1.0, (2, 16)), | |
| # 64: (1.0, (2, 8)), | |
| # 128: (1.0, (2, 6)), | |
| # }, | |
| # "256": {1: (1.0, (128, 300))}, | |
| # "512": {1: (0.5, (64, 128))}, | |
| # "480p": {1: (0.4, (32, 128)), 16: (0.4, (2, 32)), 32: (0.0, None)}, | |
| # "720p": {16: (0.1, (2, 16)), 32: (0.0, None)}, # No examples now | |
| # "1024": {1: (0.3, (8, 64))}, | |
| # "1080p": {1: (0.3, (2, 32))}, | |
| # == stage 3 == | |
| "720p": {1: (20, 40), 32: (0.5, (2, 4)), 64: (0.5, (1, 1))}, | |
| } | |
| # Define acceleration | |
| num_workers = 4 | |
| num_bucket_build_workers = 16 | |
| dtype = "bf16" | |
| grad_checkpoint = True | |
| plugin = "zero2" | |
| sp_size = 1 | |
| # Define model | |
| model = dict( | |
| type="STDiT2-XL/2", | |
| from_pretrained=None, | |
| input_sq_size=512, # pretrained model is trained on 512x512 | |
| qk_norm=True, | |
| enable_flashattn=True, | |
| enable_layernorm_kernel=True, | |
| ) | |
| vae = dict( | |
| type="VideoAutoencoderKL", | |
| from_pretrained="stabilityai/sd-vae-ft-ema", | |
| micro_batch_size=4, | |
| local_files_only=True, | |
| ) | |
| text_encoder = dict( | |
| type="t5", | |
| from_pretrained="DeepFloyd/t5-v1_1-xxl", | |
| model_max_length=200, | |
| shardformer=True, | |
| local_files_only=True, | |
| ) | |
| scheduler = dict( | |
| type="iddpm", | |
| timestep_respacing="", | |
| ) | |
| # Others | |
| seed = 42 | |
| outputs = "outputs" | |
| wandb = False | |
| epochs = 1000 | |
| log_every = 10 | |
| ckpt_every = 1000 | |
| load = None | |
| batch_size = None | |
| lr = 2e-5 | |
| grad_clip = 1.0 | |